Gestalt Pattern Recognition with Arrays of Predetermined Neural Functions

Abstract

A predetermined neural-like function which makes a ternary logical comparison to its neighbors in an array of similar functions exhibits the ability to categorize two-dimensional geometric patterns by the distinctiveness of their shape directly. This property filter is but one of a family of similar predetermined neural-like functions which exhibit Gestalt recognition characteristics. Actual constructions of individual units and digital simulation of arrays of these units have empirically supported the theoretical foundation of this work. The findings at this time are preliminary and are described here to inform the reader about the nature and scope of the work and the direction in which further work will proceed. The author feels that the demonstration of a neural-like array with Gestalt-like properties for recognizing patterns represents a step in demonstrating that the Gestalt capability of the human being may be mechanistic in nature and can eventually be implemented by artificial means. The utility of this pattern recognition system is obvious for two-dimensional projections. The economics of such a device as compared to other methods of recognition look favorable. Thus, this work not only indicates the theoretical possibility of Gestalt-like functions, but is expected to result in useful applications.